With the advent of ubiquitous computing, graphical user interface, and multimedia data exchange in business, commerce, and private use, efficient and high quality processing of visual data have become increasingly more important. Visual data include half-tone (gray-scale) images, color images, and large and small text represented in a variety of formats. Generally, visual data are displayed on a display device, such as a computer display, or other medium, such as paper, having picture elements or pixels. Density of Pixels, usually expressed as dots per inch (DPI), for example, 300 or 400 DPI, is a measure of the resolution of an image. In display applications, for example, for printing gray-scale or color text and images, it is often desirable or required (for example, because of hardware limitations in the display device or printer) to reduce the original resolution of the image without significantly adversely affecting the quality of the image. Digital scanning of a paper copy sometimes produces undesirable artifacts, such as inter-screen moire when the paper copy is printed by half-toning techniques, more fully described below. Image classification and/or segmentation may be used to first classify a type of the image to be scanned, and then select an appropriate processing technique for the particular type of image. For example, using image classification, if the image type is determined to be text, then text processing techniques, such as sharpening text edges and smoothing pre-halftoned regions may be used. Image classification techniques are computationally expensive to apply and do not always correctly identify the image type. As such, the wrong techniques may be applied to a given type of image further exacerbating image quality problems.